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Socio-economic and demographic determinants of non-communicable diseases in Kenya: a secondary analysis of the Kenya stepwise survey

INTRODUCTION: non-communicable diseases (NCDs) are projected to become the leading cause of death in Africa by 2030. Gender and socio-economic differences influence the prevalence of NCDs and their risk factors. METHODS: we performed a secondary analysis of the STEPS 2015 data to determine prevalenc...

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Autores principales: Mwangi, Kibachio Joseph, Mwenda, Valerian, Gathecha, Gladwell, Beran, David, Guessous, Idris, Ombiro, Oren, Ndegwa, Zachary, Masibo, Peninnah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The African Field Epidemiology Network 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7992900/
https://www.ncbi.nlm.nih.gov/pubmed/33796165
http://dx.doi.org/10.11604/pamj.2020.37.351.21167
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author Mwangi, Kibachio Joseph
Mwenda, Valerian
Gathecha, Gladwell
Beran, David
Guessous, Idris
Ombiro, Oren
Ndegwa, Zachary
Masibo, Peninnah
author_facet Mwangi, Kibachio Joseph
Mwenda, Valerian
Gathecha, Gladwell
Beran, David
Guessous, Idris
Ombiro, Oren
Ndegwa, Zachary
Masibo, Peninnah
author_sort Mwangi, Kibachio Joseph
collection PubMed
description INTRODUCTION: non-communicable diseases (NCDs) are projected to become the leading cause of death in Africa by 2030. Gender and socio-economic differences influence the prevalence of NCDs and their risk factors. METHODS: we performed a secondary analysis of the STEPS 2015 data to determine prevalence and correlation between diabetes, hypertension, harmful alcohol use, smoking, obesity and injuries across age, gender, residence and socio-economic strata. RESULTS: tobacco use prevalence was 13.5% (males 19.9%, females 0.9%, p<0.001); harmful alcohol use was 12.6% (males 18.1%, females 2.2%, p<0.001); central obesity was 27.9% (females 49.5%, males 32.9%, p=0.017); type 2 diabetes prevalence 3.1% (males 2.0%, females 2.8%, p=0.048); elevated blood pressure prevalence was 23.8% (males 25.1%, females 22.6%, p<0.001), non-use of helmets 72.8% (males 89.5%, females 56.0%, p=0.031) and seat belts non-use 67.9% (males 79.8%, females 56.0%, p=0.027). Respondents with <12 years of formal education had higher prevalence of non-use of helmets (81.7% versus 54.1%, p=0.03) and seat belts (73.0% versus 53.9%, p=0.039). Respondents in the highest wealth quintile had higher prevalence of type II diabetes compared with those in the lowest (5.2% versus 1.6%,p=0.008). Rural dwellers had 35% less odds of tobacco use (aOR 0.65, 95% CI 0.49, 0.86) compared with urban dwellers, those with ≥12 years of formal education had 89% less odds of tobacco use (aOR 0.11, 95% CI 0.07, 0.17) compared with <12 years, and those belonging to the wealthiest quintile had 64% higher odds of unhealthy diets (aOR 1.64, 95% CI 1.26, 2.14). Only 44% of respondents with type II diabetes and 16% with hypertension were aware of their diagnosis. CONCLUSION: prevalence of NCD risk factors is high in Kenya and varies across socio-demographic attributes. Socio-demographic considerations should form part of multi-sectoral, integrated approach to reduce the NCD burden in Kenya.
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spelling pubmed-79929002021-03-31 Socio-economic and demographic determinants of non-communicable diseases in Kenya: a secondary analysis of the Kenya stepwise survey Mwangi, Kibachio Joseph Mwenda, Valerian Gathecha, Gladwell Beran, David Guessous, Idris Ombiro, Oren Ndegwa, Zachary Masibo, Peninnah Pan Afr Med J Research INTRODUCTION: non-communicable diseases (NCDs) are projected to become the leading cause of death in Africa by 2030. Gender and socio-economic differences influence the prevalence of NCDs and their risk factors. METHODS: we performed a secondary analysis of the STEPS 2015 data to determine prevalence and correlation between diabetes, hypertension, harmful alcohol use, smoking, obesity and injuries across age, gender, residence and socio-economic strata. RESULTS: tobacco use prevalence was 13.5% (males 19.9%, females 0.9%, p<0.001); harmful alcohol use was 12.6% (males 18.1%, females 2.2%, p<0.001); central obesity was 27.9% (females 49.5%, males 32.9%, p=0.017); type 2 diabetes prevalence 3.1% (males 2.0%, females 2.8%, p=0.048); elevated blood pressure prevalence was 23.8% (males 25.1%, females 22.6%, p<0.001), non-use of helmets 72.8% (males 89.5%, females 56.0%, p=0.031) and seat belts non-use 67.9% (males 79.8%, females 56.0%, p=0.027). Respondents with <12 years of formal education had higher prevalence of non-use of helmets (81.7% versus 54.1%, p=0.03) and seat belts (73.0% versus 53.9%, p=0.039). Respondents in the highest wealth quintile had higher prevalence of type II diabetes compared with those in the lowest (5.2% versus 1.6%,p=0.008). Rural dwellers had 35% less odds of tobacco use (aOR 0.65, 95% CI 0.49, 0.86) compared with urban dwellers, those with ≥12 years of formal education had 89% less odds of tobacco use (aOR 0.11, 95% CI 0.07, 0.17) compared with <12 years, and those belonging to the wealthiest quintile had 64% higher odds of unhealthy diets (aOR 1.64, 95% CI 1.26, 2.14). Only 44% of respondents with type II diabetes and 16% with hypertension were aware of their diagnosis. CONCLUSION: prevalence of NCD risk factors is high in Kenya and varies across socio-demographic attributes. Socio-demographic considerations should form part of multi-sectoral, integrated approach to reduce the NCD burden in Kenya. The African Field Epidemiology Network 2020-12-16 /pmc/articles/PMC7992900/ /pubmed/33796165 http://dx.doi.org/10.11604/pamj.2020.37.351.21167 Text en Copyright: Kibachio Joseph Mwangi et al. https://creativecommons.org/licenses/by/4.0 The Pan African Medical Journal (ISSN: 1937-8688). This is an Open Access article distributed under the terms of the Creative Commons Attribution International 4.0 License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Mwangi, Kibachio Joseph
Mwenda, Valerian
Gathecha, Gladwell
Beran, David
Guessous, Idris
Ombiro, Oren
Ndegwa, Zachary
Masibo, Peninnah
Socio-economic and demographic determinants of non-communicable diseases in Kenya: a secondary analysis of the Kenya stepwise survey
title Socio-economic and demographic determinants of non-communicable diseases in Kenya: a secondary analysis of the Kenya stepwise survey
title_full Socio-economic and demographic determinants of non-communicable diseases in Kenya: a secondary analysis of the Kenya stepwise survey
title_fullStr Socio-economic and demographic determinants of non-communicable diseases in Kenya: a secondary analysis of the Kenya stepwise survey
title_full_unstemmed Socio-economic and demographic determinants of non-communicable diseases in Kenya: a secondary analysis of the Kenya stepwise survey
title_short Socio-economic and demographic determinants of non-communicable diseases in Kenya: a secondary analysis of the Kenya stepwise survey
title_sort socio-economic and demographic determinants of non-communicable diseases in kenya: a secondary analysis of the kenya stepwise survey
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7992900/
https://www.ncbi.nlm.nih.gov/pubmed/33796165
http://dx.doi.org/10.11604/pamj.2020.37.351.21167
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